CN116125027A - Sewage on-line monitoring system and method based on Internet of things - Google Patents
Sewage on-line monitoring system and method based on Internet of things Download PDFInfo
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- CN116125027A CN116125027A CN202310379327.3A CN202310379327A CN116125027A CN 116125027 A CN116125027 A CN 116125027A CN 202310379327 A CN202310379327 A CN 202310379327A CN 116125027 A CN116125027 A CN 116125027A
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- G08—SIGNALLING
- G08B—SIGNALLING OR CALLING SYSTEMS; ORDER TELEGRAPHS; ALARM SYSTEMS
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Abstract
The invention discloses a sewage online monitoring system and method based on the Internet of things, which relate to the technical field of sewage monitoring and comprise the following steps: the monitoring unit, the evaluation unit and the judging unit are used for evaluating the water pollution degree based on the water pollution data in the water body area, and sending an early warning to a user when the area exceeds half of the bearing line; the early warning unit is used for reducing pollutants in the water body area, and if the expected effect cannot be achieved, the biological community is driven away from the area; when a user does not effectively treat the water pollution source, judging whether the water pollution is spread to other areas, and if the spread trend exceeds the expected trend, alarming the change of the water quality; when the water pollution is monitored on line, whether the water pollution can affect the survival of biological communities in the water is judged, if so, an early warning is sent to the outside to remind a user to treat the water, and further deepening of the water pollution is avoided.
Description
Technical Field
The invention relates to the technical field of sewage monitoring, in particular to a sewage online monitoring system and method based on the Internet of things.
Background
The sewage treatment station is used for treating production and domestic sewage, reaches the specified emission standard, and is an important facility for protecting the environment. For these sewage treatment stations to function truly, it is also necessary to ensure by strict emission regimes, organizations and regulatory regimes.
When the water quality of the water source is monitored by the existing sewage on-line monitoring system, the water quality of the water source is generally only considered, the water source is treated uniformly, the living state of common organisms in the water body is difficult to consider, and when the water quality of the water source is poor and exceeds the warning threshold value, the water source is treated once, so that a biological community in the water body, especially economic crops, can be subjected to great attack due to severe change of the water quality.
Therefore, the invention provides an online sewage monitoring system and method based on the Internet of things.
Disclosure of Invention
(one) solving the technical problems
Aiming at the defects of the prior art, the invention provides a sewage on-line monitoring system and a sewage on-line monitoring method based on the Internet of things, which are used for evaluating the pollution degree of a water body based on water pollution data in the water body area by arranging a monitoring unit and an evaluation unit, and sending an early warning to a user when the area exceeds half of a bearing line; the early warning unit is used for reducing pollutants in the water body area, and if the expected effect cannot be achieved, the biological community is driven away from the area; the judging unit is used for judging whether the water pollution is spread to other areas or not when the user does not effectively treat the water pollution source, and alarming the change of the water quality if the spreading trend exceeds the expected value; pollution is generated in the water body, when the water body pollution is monitored on line, whether the water body pollution can influence the survival of biological communities in the water body is judged, if the water body pollution can be generated, an early warning is sent to the outside to remind a user to treat, the further deepening of the water body pollution is avoided, and the problem in the background technology is solved.
(II) technical scheme
In order to achieve the above purpose, the invention is realized by the following technical scheme: an online sewage monitoring method based on the Internet of things comprises the steps of,
step 1, monitoring water pollution, and after monitoring data are obtained, sending an early warning to the outside when the water pollution degree exceeds half of a set biological community bearing line;
the step 1 comprises the following steps: step 101, arranging a monitoring system in a sewage area, detecting biological communities in the water body, determining information of each biological community in the water body area, and judging a bearing line of each biological community on water pollution; 102, arranging a plurality of floating water quality detectors in a water body coverage area, detecting the water pollution degree of the water body, and obtaining a plurality of groups of water pollution data; step 103, judging whether the content of each component in the water pollution data exceeds half of the biological community bearing line or not based on the acquired water pollution data, and if so, giving an alarm;
step 2, evaluating the water pollution degree based on water pollution data in the water body area, dividing the monitored water body into a plurality of areas, predicting the change trend of the water pollution data in the plurality of areas, and sending an early warning to a user when the area exceeds half of the bearing line;
step 3, taking measures for reducing the water pollution number in the water quality heavy pollution area according to the sent early warning, and reducing pollutants in the water body area, if the expected effect cannot be achieved, driving the biological community out of the area; reminding a user to treat the water pollution source when the proportion of the safety area is smaller than the safety threshold value;
step 4, judging whether the water pollution is spread to other areas or not when the user does not effectively treat the water pollution source, and determining the spreading trend if the water pollution is spread; if the spreading trend exceeds the expected value, alarming the change of the water quality;
and 5, evaluating the safety of the water body area, and sending an alarm to the outside when the evaluation result shows that the water body environment has danger.
Further, step 103 further includes: 104, determining the area with the most serious water pollution degree from a plurality of groups of water pollution data, recording the area as a water pollution source, and outputting the position of the water pollution source; judging the position of a biological community in the water body by using a monitoring system, detecting the distance between the biological community and a water pollution source, and outputting the distance;
step 105, obtaining the distance between the biological community and the water pollution source, and judging whether the distance is smaller than a preset safety distance; if the water pollution source is smaller than the water pollution source, a dispersion instruction is sent to the biological community, and the biological community is driven away from the water pollution source.
Further, the step 2 includes the following: step 201, based on a plurality of groups of acquired water pollution data, evaluating the water pollution degree corresponding to a water area corresponding to a floating water quality detector to acquire a water quality evaluation value;
step 202, determining a first water quality threshold value and a second water quality threshold value of water quality, and dividing a water body into a heavy pollution area, a light pollution area and a safety area; and (3) combining the trained classification model with the water quality evaluation value and the corresponding position, dividing the water body into a plurality of areas, and defining boundaries among the areas.
Further, step 202 further includes: step 203, based on the change trend of a plurality of groups of water pollution data, performing function fitting by using a nonlinear least square method, and representing the change trend of the pollution factor content in the safety area in a function mode;
204, predicting the concentration of the next moment in the area according to the water pollution data change fitting function, sending out early warning if the predicted value is higher than a first water quality threshold value, and determining the time when the predicted value reaches the first water quality threshold value; and if the predicted value is higher than the second water quality threshold value, sending out early warning and determining the time for reaching the second water quality threshold value.
Further, the step 3 includes: step 301, receiving early warning information, and increasing the working power of the aerator and the filtering equipment through a set controller when a user does not process the early warning; step 302, detecting the water body according to the floating water quality detector, judging whether the water pollution degree is further increased, and if the water pollution degree is still continuously increased, judging the water body area of which the water quality evaluation value exceeds the second water quality threshold value in the safety area at the next moment by the floating water quality detector.
Further, step 302 further includes: step 303, obtaining the ratio of the unsafe area to the water body area, and comparing the ratio with a corresponding preset threshold value to obtain a comparison result; reminding a user to treat the water pollution source when the duty ratio of the safety area is smaller than a set safety threshold value; when the safe area is converted into the light pollution area, the biological community contained in the safe area is driven away;
step 304, monitoring the position of the biological community, determining the safe distance between the water pollution source and the biological community, and if the safe distance is within the corresponding distance threshold, increasing the working power of at least one of the aerator and the filtering device according to a preset proportion.
Further, step 4 includes: step 401, detecting a water body, obtaining water pollution data output by a floating water quality detector at each position, and marking positions forming the water pollution data; based on water pollution data at each position of the water body, acquiring a plurality of water quality evaluation values, and connecting the positions with equal water quality evaluation values of the water body together to form an equal pollution line;
step 402, judging that the pollution is spreading and the protruding direction of the equal pollution lines is the pollution spreading direction if the number of the equal pollution lines with the water quality evaluation value higher than the second water quality threshold value is increased according to the change of the shape and the density of the equal pollution lines.
Further, step 402 includes, after: step 403, acquiring area data of the water body safety area at a plurality of moments, and performing function fitting on the area change trend of the water body safety area to form a water pollution spreading fitting function;
based on the water pollution spreading fitting function, determining the area occupation ratio of the water body safety area at the next moment, and alarming to a user after the area occupation ratio exceeds an alarm threshold;
step 404, determining the position of a biological community in a safety area through a monitoring system, and judging the time required to be consumed for covering the water pollution to the area by combining the water pollution spreading trend to form a first preset time;
step 405, after a first preset time, determining a plurality of areas not higher than the bearing line in the water body, and determining at least one of the areas closest to the water body outlet, and guiding the biota to fall in the safe area to transfer to the water body outlet through the feeding system.
Further, the step 5 includes the following: step 501, when the pollutant concentration exceeds the bearing line, if the pollutant concentration is still increasing, comprehensively evaluating the pollution degree of the water body to form a safety evaluation value;
step 502, comparing the safety evaluation value with an alert threshold value, judging whether the safety evaluation value is within the alert threshold value, if the safety evaluation value is within the alert threshold value, temporarily avoiding harm to the water body, and preferentially protecting the biological community; if the water is beyond the warning threshold, the water is endangered, an alarm is given to the outside, and the water is treated preferentially;
step 503, after a second preset time, re-judging the water quality evaluation value of the water body, and gradually putting the biological community into the water body, namely putting the fish shoals, according to a preset amount if the water quality evaluation value is falling and is lower than a second water quality threshold value; if the water pollution data concentration does not drop, an alarm is issued.
Sewage on-line monitoring system based on thing networking includes:
the monitoring unit is used for monitoring the water pollution, and sending an early warning to the outside when the water pollution degree exceeds half of a set biological community bearing line after the monitoring data are acquired;
the assessment unit is used for assessing the water pollution degree based on the water pollution data in the water body area, and sending an early warning to a user when the area exceeds half of the bearing line;
the early warning unit is used for reducing pollutants in the water body area, and if the expected effect cannot be achieved, the biological community is driven away from the area to remind a user to treat the water pollution source;
the judging unit is used for judging whether the water pollution is spread to other areas or not when the user does not effectively treat the water pollution source, and determining the spreading trend if the water pollution is spread; if the spreading trend exceeds the expected value, alarming the change of the water quality;
and the alarm unit is used for evaluating the safety of the water body area and sending an alarm to the outside when the evaluation result shows that the water body environment has danger.
(III) beneficial effects
The invention provides a sewage online monitoring system and method based on the Internet of things, which have the following beneficial effects:
when the water pollution is monitored on line, whether the water pollution can affect the survival of biological communities in the water is judged, if so, an early warning is sent to the outside to remind a user to treat the water, and further deepening of the water pollution is avoided.
When the user fails to make treatment in time, continuing to judge the change trend of the water pollution, and if the water quality of the water reaches the bearing line, reminding the user, and simultaneously guiding the transfer of the biological community or driving the biological community away so as to avoid a great deal of damage caused by the water pollution;
when the water pollution area is large, the water quality of the water body is automatically adjusted, the living condition of the biological community is improved as much as possible, if the treatment is invalid, the biological community is actively driven away, and an early warning is sent out again, when the user does not treat the water pollution yet, if the water pollution is spread to other areas, whether the water pollution data cause damage to the biological community is judged, and if the potential safety hazard exists, the biological community is guided to be transferred to the outside of the water body.
After the water body is pre-warned for many times and properly treated, whether the water body is safe or not is judged, if the water body is unsafe, the user is directly bypassed, the alarm is given to the outside, and a unit capable of treating the water body pollution is searched for treatment when the surrounding environment and even the human health are influenced.
The method combines the early warning and the alarming for a plurality of times, can not only acquire original data while carrying out on-line monitoring on the water body, but also evaluate and judge the water body pollution, ensure the biological safety in the water body environment and the surrounding environmental safety, and carry out early warning for a plurality of times, timely prevent the spread of the water body pollution, and verify the monitoring accuracy through the biological community in the water.
Drawings
FIG. 1 is a schematic diagram of a sewage on-line monitoring method based on the Internet of things;
fig. 2 is a schematic structural diagram of the sewage on-line monitoring system based on the internet of things.
In the figure: 10. a monitoring unit; 20. an evaluation unit; 30. an early warning unit; 40. a judging unit; 50. and an alarm unit.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Referring to fig. 1-2, the invention provides an online sewage monitoring method based on the internet of things, which comprises the following steps: step 1, monitoring water pollution, and after monitoring data are obtained, sending an early warning to the outside when the water pollution degree exceeds half of a set biological community bearing line; the step 1 comprises the following steps:
step 101, arranging a monitoring system in a sewage area, detecting biological communities in the water body, determining information of each biological community in the water body area, and judging the bearing degree of each biological community on water pollution, namely bearing lines;
in practice, most common biological communities in the water body are often not more, most aquatic organisms, particularly fish, can roughly judge the type through judging the body type, and the bearing degree of the type on the water pollution can be obtained through retrieval and also can be judged through national standards; the pollution factors related to water pollution are more, such as total nitrogen, total phosphorus, ammonia nitrogen, dissolved oxygen of water, COD and ammonia nitrogen, etc.
However, considering that in the present solution, when the water pollution is monitored online, the influence on the biological community in the water, namely, the influence on the fish shoal, needs to be considered, and in order to reduce the difficulty of the evaluation, only a few pollution factors are selected when the water quality evaluation value is formed to evaluate the water quality, and the pollution factors may be different from other evaluation methods in the part, but if the evaluation method is replaced, the integrity of the present concept is not actually affected.
102, arranging a plurality of floating water quality detectors in a water body coverage area, detecting the water pollution degree of the water body, and obtaining a plurality of groups of water pollution data;
step 103, judging whether the content of each component in the water pollution data exceeds half of the biological community bearing line or not based on the acquired water pollution data, and if so, giving an alarm; if more than half of the biological community is subjected to the line, it means that the water environment has begun to be unadapted to the survival of the biological community;
104, determining the area with the most serious water pollution degree from a plurality of groups of water pollution data, recording the area as a water pollution source, and outputting the position of the water pollution source; judging the position of a biological community in the water body, namely the position of a fish school by using scanning or imaging equipment, namely a monitoring system, detecting the distance between the biological community and a water pollution source, and outputting the distance;
step 105, obtaining the distance between the biological community and the water pollution source, and judging whether the distance is smaller than a preset safety distance; detecting water pollution data of the place where the biological community is located by using a floating water quality detector, and judging whether the water pollution data exceeds half of a bearing line or not; when at least one of the two conditions exceeds, a dispersing instruction is sent to the biological community in the water body to drive the biological community away from the water pollution source; thereby reducing the harm of the water pollution source to the biological community in the water body.
When the device is used, the contents in the steps 101 to 105 are combined, a plurality of floating water quality detectors are arranged in a water body, water pollution data in the water body are monitored, and the detection result is compared with a half of a bearing line of a biological community, particularly a fish school; if the concentration of pollutants in the water body is higher than half of the bearing line, the Li Yongpiao floating water quality detector means that the water body has water pollution, and the water quality detector gives an alarm to the user based on the Internet of things to remind the user to treat the water body early, so that the water body is improved, and the living condition of a biological community in the water body is improved. And by judging the positions of the biological communities, when the biological communities wander to the water body with larger pollution, the biological communities are dispersed, so that irreversible damage to the biological communities caused by the polluted water body is avoided.
Further, considering that after the water pollution source exists in the water body, the water pollution source can be continuously diffused in the water body under the action of external force or along with the fluctuation of the water body, so that the pollution conditions of the water body can be greatly different; on the one hand, if the floating type water quality detector is not uniform enough, a certain gap exists between the acquired water pollution data and the actual water situation, and on the other hand, the biological community is difficult to transfer orderly according to the pollution degree of the water quality.
Step 2, evaluating the water pollution degree based on water pollution data in the water body area, dividing the monitored water body into a plurality of areas, predicting the change trend of the water pollution data in the plurality of areas, and sending an early warning to a user when the area exceeds half of the bearing line;
the step 2 comprises the following steps:
step 201, based on the acquired several groups of water pollution data, evaluating the water pollution degree corresponding to the water area corresponding to the floating water quality detector to acquire a water quality evaluation value P; wherein the acquired pollution data comprises: the ammonia nitrogen amount N, the total phosphorus amount ZP and the chemical oxygen demand COD in the water body; the method for forming the water quality evaluation value P comprises the following steps:
the method comprises the steps of obtaining ammonia nitrogen N, total phosphorus ZP and chemical oxygen demand COD in a water body, carrying out normalization treatment, and synthesizing to form a water quality evaluation value P, wherein the confirmation logic of the water quality evaluation value P is as follows:
wherein, the liquid crystal display device comprises a liquid crystal display device,
、/>
、/>
is a changeable constant parameter, wherein +.>
And is also provided with
The user can adjust the C and D constant correction coefficients according to the actual conditions, and can correct the C and D constant correction coefficients according to the actual pollution identification conditions.
It is emphasized that there are several methods of evaluating the water quality, and for one of the above-defined methods, only the water quality can be evaluated in view of convenience, and if there are other more effective ways, several factors can be associated together to form the water quality evaluation value P, and the method can also be adopted or replaced.
When the water quality of the water body reaches a bearing line, determining the size of a water quality evaluation value P of the water body, thereby determining a first water quality threshold value of the water quality evaluation value P, namely a first evaluation value P1, and when the water quality evaluation value P exceeds the first water quality threshold value, namely that the biological community in the water body is difficult to survive, and the related area is determined as a heavy pollution area;
correspondingly, determining a second water quality threshold value of the water quality evaluation value P, namely a second evaluation value P2 based on the water quality evaluation value P of the water body when the water quality of the water body reaches half of the bearing line, and determining the related area as a light pollution area when the water quality evaluation value P exceeds the second water quality threshold value, namely that the living difficulty of the biological community in the water body begins to increase gradually; and the non-polluted area in the water body is a safe area.
And when the value of the water quality evaluation value P of the water body exceeds the second water quality threshold value, an alarm is sent to a user.
Step 202, combining the water quality evaluation value P and the corresponding position by the trained classification model, dividing the water body into a plurality of areas, and defining boundaries among the areas; sequencing and marking the areas according to the size of the water quality evaluation value P;
step 203, after the area differentiation of the water body is completed, determining an area in which the water quality evaluation value P is not higher than a first water quality threshold value, and determining the area as a safe area; based on the change trend of a plurality of groups of water pollution data, performing function fitting by a nonlinear least square method, and representing the change trend of the pollution factor content in the safety area in a function mode;
204, predicting the concentration of the next moment in the area according to the water pollution data change fitting function, sending out early warning if the predicted value is higher than a first water quality threshold value, and determining the time when the predicted value reaches the first water quality threshold value; if the predicted value is higher than the second water quality threshold value, sending out early warning and determining the time reaching the second water quality threshold value;
therefore, a user can know how much time can be processed, whether things are urgent or not is judged, when the water pollution monitoring device is used, in combination with the steps 201 to 204, water pollution data in a water body area are monitored by utilizing the floating water quality detector, and according to the acquired water pollution data of a plurality of groups, change data of water pollution data concentration are predicted based on a water pollution data fitting function.
Judging whether the water body area is suitable for living of the biological community represented by the fish shoal according to the ratio of the predicted value to the first water quality threshold value and the second water quality threshold value, if the water pollution data is higher than the second water quality threshold value, dispersing the biological community in the area, and keeping the biological community in the area away; so as to avoid the influence of the polluted water body on the biological community.
Step 3, taking measures for reducing the water pollution number in the water quality heavy pollution area according to the sent early warning, and reducing pollutants in the water body area, if the expected effect cannot be achieved, driving the biological community out of the area; reminding a user to treat the water pollution source when the proportion of the safety area is smaller than the safety threshold value;
the step 3 comprises the following steps:
step 301, receiving early warning information, and increasing the working power of the aerator and the filtering equipment through a set controller when a user does not process the early warning; the equipment capable of improving the water body is started, so that when the user does not treat the water body, the water body can be automatically treated.
Step 302, detecting the water body according to the floating water quality detector, judging whether the water pollution degree is further increased, and if the water pollution degree is still continuously increased, judging the water body area of which the water quality evaluation value P exceeds a second water quality threshold value in a safety area at the next moment through the floating water quality detector;
step 303, obtaining the ratio of the unsafe area to the water body area, and comparing the ratio with a corresponding preset threshold value to obtain a comparison result; reminding a user to treat the water pollution source when the duty ratio of the safety area is smaller than a set safety threshold value, for example, 20%;
when the safe area is converted into the light pollution area, the biological community contained in the safe area is driven away; thereby judging whether the treatment of the water body has an effect.
In use, in combination with steps 301 to 303, when the water pollution level in the water body area is further increased, the water pollution area is determined, and when the water pollution area ratio exceeds a safety threshold, the video monitoring system and the feeding system are used for guiding the biological community to transfer so as to maintain a certain distance from the water pollution source to ensure safety.
Step 304, monitoring the position of the biological community, determining the safe distance between the water pollution source and the biological community, and if the safe distance is within the corresponding distance threshold, increasing the working power of at least one of the aerator and the filtering device according to a preset proportion.
Thereby rapidly relieving the water pollution and maintaining the survival of the biological community in the water body before the water body is comprehensively treated. When the unsafe area of the water body is more, the water pollution in the water body area can be severe, the biological community needs to be guided to leave the water pollution area rapidly at the moment so as to protect the safety of the user, and meanwhile, the user can be reminded of treating the water pollution source, so that pollutants at the water pollution source are prevented from continuously spreading to other areas outside the water body, and the water body integrity is deteriorated.
In combination with the content in the step 3, when the water pollution in the water body area is serious, the biological community in the water body area can be driven and guided, and the biological community is transferred into a safe area, so that the safety of the biological community is ensured; in contrast, if a large amount of the biotope represented by fish shoals is collected in a certain area, it can be determined that the water pollution level in the area is limited.
However, it is also considered that the water pollution source is treated, for example, after the water pollution source is turned off, the discharged pollutant does not disappear, and if the treatment is not timely performed, the pollutant in the pollution source area can further spread to other areas, for example, the pollutant spreads from the heavy pollution area to the light pollution area, and the light pollution area is transferred to the safe area; also based on this, the spread of contaminated areas needs to be taken into account when monitoring the body of water. Therefore, step 3 is also followed by step 4;
step 4, judging whether the water pollution is spread to other areas or not when the user does not effectively treat the water pollution source, and determining the spreading trend if the water pollution is spread; if the spreading trend exceeds the expected value, alarming the change of the water quality; step 4 comprises the following contents:
step 401, detecting a water body, obtaining water pollution data output by a floating water quality detector at each position, and marking positions forming the water pollution data; based on water pollution data at each position of the water body, acquiring a plurality of water quality evaluation values P, and connecting the positions of the water body, where the water quality evaluation values P are equal, together to form an equal pollution line;
step 402, judging that the pollution is spreading and the protruding direction of the equal pollution lines is the pollution spreading direction if the number of the equal pollution lines with the water quality evaluation value P higher than the second water quality threshold value is increased according to the change of the shape and the density of the equal pollution lines;
step 403, acquiring area data of the water body safety area at a plurality of moments, and performing function fitting on the area change trend of the water body safety area to form a water pollution spreading fitting function; based on the water pollution spread fitting function, the area occupation ratio of the water body safety area at the next moment is determined, and after the area occupation ratio exceeds the warning threshold value, for example, 15%, the user is warned.
When the method is used, the spreading of the water pollution is characterized in a function fitting mode, the change of the spreading area of the water pollution can be predicted, and if the spreading area of the water pollution exceeds the expected value or the spreading of the water pollution is too fast, the method means that the safety of the water is lower and lower, and the water needs to be treated immediately by a user.
Step 404, determining the position of a biological community in a safety area through a monitoring system, and judging the time required to be consumed for covering the water pollution to the area by combining the water pollution spreading trend to form a first preset time;
step 405, after a first preset time, determining a plurality of areas not higher than the bearing line in the water body, and determining at least one of the areas closest to the water body outlet, and guiding the biota to fall in the safe area to transfer to the water body outlet through the feeding system.
When the water pollution monitoring system is used, after the spreading trend of the water pollution area is determined, the monitoring system is matched to judge whether a biological community exists in the pollution area, if the biological community exists, the biological community is guided to a safe area when the water pollution degree possibly damages the biological community, survival of the biological community is guaranteed preferentially, if the water pollution degree is still aggravated, the biological community can be guided to other water bodies without water pollution, and water pollution sources of the water body are also convenient to process.
After step 4, whether the biological community is in a safe condition or not, the pollution condition in the water body is evaluated, the water pollution is prevented from spreading too much, or the water pollution degree is further increased, and the soil or surrounding residents are influenced or dangerous, so that step 5 is further arranged after step 4.
Step 5, evaluating the safety of the water body area, and sending an alarm to the outside when the evaluation result shows that the water body environment has danger; the step 5 comprises the following steps:
step 501, when the pollutant concentration exceeds the bearing line, if the pollutant concentration is still increasing, comprehensively evaluating the pollution degree of the water body to form a safety evaluation value;
the method of forming the security evaluation value RF is as follows: the method comprises the steps of acquiring the water body oxygen concentration Op, the water body polluted safety area Am and the water quality evaluation value P by matching with an oxygen concentration sensor, carrying out normalization processing, and forming a safety evaluation value RF after comprehensive evaluation; the method for correlating the security evaluation value RF is as follows:
wherein, the liquid crystal display device comprises a liquid crystal display device,
，/>
and->
，/>
、/>
Is weight(s)>
The specific value of the constant correction coefficient can be set by user adjustment or generated by fitting an analysis function; wherein R is a correlation coefficient between the area Am of the water body polluted safe area and the water quality evaluation value P, and is obtained by carrying out correlation calculation on the areas Am of the water body polluted safe area and the water quality evaluation value P.
Step 502, comparing the safety evaluation value RF with an alert threshold value, judging whether the safety evaluation value RF is within the alert threshold value, if the safety evaluation value RF is within the alert threshold value, the water body is temporarily harmless, and the biological community is protected preferentially; if the water is beyond the warning threshold, the water is already jeopardized, an alarm is sent to the outside, and the water is treated preferentially.
It is emphasized that there are several methods of evaluating water quality safety, and for one of the above-defined methods, only the water quality safety is evaluated in view of convenience, and if there are other more efficient ways, several factors can be associated together to form the water quality evaluation value P, and the method of forming the water quality evaluation value P can also be adopted or replaced, if other water quality safety schemes are replaced, the implementation of the whole scheme is not affected substantially, and the concept of the scheme is not conflicting.
In combination with step 501 and step 502, based on the collection of the water oxygen concentration Op, the water pollution safety area Am and the water quality evaluation value P, the water safety is evaluated, so that the formed safety evaluation value RF quantifies the water safety, and the water pollution is prevented from damaging the surrounding environment under the data of permission of the conditions.
Step 503, after a second preset time, re-judging the water quality evaluation value P of the water body, and gradually putting the biological community into the water body, namely putting the fish shoal, according to a preset amount if the water quality evaluation value P is falling and is lower than a second water quality threshold value; if the water pollution data concentration does not drop, an alarm is issued.
Referring to fig. 1-2, the present invention provides an online sewage monitoring system based on internet of things, comprising:
the monitoring unit 10 monitors the water pollution, and after acquiring monitoring data, when the water pollution degree exceeds half of the bearing line of the set biological community, the monitoring unit sends an early warning to the outside;
the evaluation unit 20 is used for evaluating the water pollution degree based on the water pollution data in the water body area, and sending an early warning to a user when the area exceeds half of the bearing line;
the early warning unit 30 is used for reducing pollutants in the water body area, and if the expected effect cannot be achieved, the biological community is driven away from the area to remind a user of treating the water pollution source;
a judging unit 40 for judging whether the water pollution has spread to other areas when the user does not perform effective treatment on the water pollution source, and determining a spreading trend if the water pollution has spread; if the spreading trend exceeds the expected value, alarming the change of the water quality;
the alarm unit 50 evaluates the safety of the water body region and gives an alarm to the outside when the evaluation result shows that the water body environment has danger.
In the present application, in combination with the contents in step 1 and step 5, there are at least the following effects:
pollution is generated in the water body, when the water body pollution is monitored on line, whether the water body pollution can influence the survival of biological communities in the water body is judged, if the water body pollution can be generated, an early warning is sent to the outside, the user is reminded to process, and further deepening of the water body pollution is avoided.
When the user fails to make treatment in time, continuing to judge the change trend of the water pollution, and if the water quality of the water reaches the bearing line, reminding the user, and simultaneously guiding the transfer of the biological community or driving the biological community away so as to avoid a great deal of damage caused by the water pollution;
when the water pollution area is large, the water quality of the water body is automatically adjusted, the living condition of the biological community is improved as much as possible, if the treatment is invalid, the biological community is actively driven away, and an early warning is sent out again, when the user does not treat the water pollution yet, if the water pollution is spread to other areas, whether the water pollution data cause damage to the biological community is judged, and if the potential safety hazard exists, the biological community is guided to be transferred to the outside of the water body.
After the water body is pre-warned for many times and properly treated, whether the water body is safe or not is judged, if the water body is unsafe, the user is directly bypassed, the alarm is given to the outside, and a unit capable of treating the water body pollution is searched for treatment when the surrounding environment and even the human health are influenced.
The method combines the early warning and the alarming for a plurality of times, can not only acquire original data while carrying out on-line monitoring on the water body, but also evaluate and judge the water body pollution, ensure the biological safety in the water body environment and the surrounding environmental safety, and carry out early warning for a plurality of times, timely prevent the spread of the water body pollution, and verify the monitoring accuracy through the biological community in the water.
The above embodiments may be implemented in whole or in part by software, hardware, firmware, or any other combination. When implemented in software, the above-described embodiments may be implemented in whole or in part in the form of a computer program product. The computer program product comprises one or more computer instructions or computer programs.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
The foregoing is merely specific embodiments of the present application, but the scope of the present application is not limited thereto, and any person skilled in the art can easily think about changes or substitutions within the technical scope of the present application, and the changes and substitutions are intended to be covered by the scope of the present application. Therefore, the protection scope of the present application shall be subject to the protection scope of the claims.
Claims (10)
1. The online sewage monitoring method based on the Internet of things is characterized by comprising the following steps of: comprising the steps of (a) a step of,
step 1, monitoring water pollution, and after monitoring data are obtained, sending an early warning to the outside when the water pollution degree exceeds half of a set biological community bearing line;
the step 1 comprises the following steps: step 101, arranging a monitoring system in a sewage area, detecting biological communities in the water body, determining information of each biological community in the water body area, and judging a bearing line of each biological community on water pollution; 102, arranging a plurality of floating water quality detectors in a water body coverage area, detecting the water pollution degree of the water body, and obtaining a plurality of groups of water pollution data; step 103, judging whether the content of each component in the water pollution data exceeds half of the biological community bearing line or not based on the acquired water pollution data, and if so, giving an alarm;
step 2, evaluating the water pollution degree based on water pollution data in the water body area, dividing the monitored water body into a plurality of areas, predicting the change trend of the water pollution data in the plurality of areas, and sending an early warning to a user when the area exceeds half of the bearing line;
step 3, taking measures for reducing the water pollution number in the water quality heavy pollution area according to the sent early warning, and reducing pollutants in the water body area, if the expected effect cannot be achieved, driving the biological community out of the area; reminding a user to treat the water pollution source when the proportion of the safety area is smaller than the safety threshold value;
step 4, judging whether the water pollution is spread to other areas or not when the user does not effectively treat the water pollution source, and determining the spreading trend if the water pollution is spread; if the spreading trend exceeds the expected value, alarming the change of the water quality;
and 5, evaluating the safety of the water body area, and sending an alarm to the outside when the evaluation result shows that the water body environment has danger.
2. The online sewage monitoring method based on the internet of things according to claim 1, wherein the method comprises the following steps: step 103 further comprises: 104, determining the area with the most serious water pollution degree from a plurality of groups of water pollution data, recording the area as a water pollution source, and outputting the position of the water pollution source; judging the position of a biological community in the water body by using a monitoring system, detecting the distance between the biological community and a water pollution source, and outputting the distance;
step 105, obtaining the distance between the biological community and the water pollution source, and judging whether the distance is smaller than a preset safety distance; if the water pollution source is smaller than the water pollution source, a dispersion instruction is sent to the biological community, and the biological community is driven away from the water pollution source.
3. The online sewage monitoring method based on the internet of things according to claim 1, wherein the method comprises the following steps: the step 2 comprises the following steps: step 201, based on a plurality of groups of acquired water pollution data, evaluating the water pollution degree corresponding to a water area corresponding to a floating water quality detector to acquire a water quality evaluation value;
step 202, determining a first water quality threshold and a second water quality threshold of water quality, wherein the first water quality threshold is higher than the second water quality threshold, determining the water body as a heavy pollution area when the water quality exceeds the first water quality threshold, determining the water body as a light pollution area when the water quality is between the first water quality threshold and the second water quality threshold, and determining the water body as a safe area when the water quality is lower than the second water quality threshold;
and (3) combining the trained classification model with the water quality evaluation value and the corresponding position, dividing the water body into a plurality of areas, and defining boundaries among the areas.
4. The online sewage monitoring method based on the internet of things according to claim 3, wherein the method comprises the following steps of: step 202 is followed by: step 203, based on the change trend of a plurality of groups of water pollution data, performing function fitting by using a nonlinear least square method, and representing the change trend of the pollution factor content in the safety area in a function mode;
204, predicting the concentration of the next moment in the area according to the water pollution data change fitting function, sending out early warning if the predicted value is higher than a first water quality threshold value, and determining the time when the predicted value reaches the first water quality threshold value; and if the predicted value is higher than the second water quality threshold value, sending out early warning and determining the time for reaching the second water quality threshold value.
5. The online sewage monitoring method based on the internet of things according to claim 1, wherein the method comprises the following steps: the step 3 comprises the following steps: step 301, receiving early warning information, and increasing the working power of the aerator and the filtering equipment through a set controller when a user does not process the early warning; step 302, detecting the water body according to the floating water quality detector, judging whether the water pollution degree is further increased, and if the water pollution degree is still continuously increased, judging the water body area of which the water quality evaluation value exceeds the second water quality threshold value in the safety area at the next moment by the floating water quality detector.
6. The online sewage monitoring method based on the internet of things according to claim 5, wherein the method comprises the following steps: step 302 is followed by: step 303, obtaining the ratio of the unsafe area to the water body area, and comparing the ratio with a corresponding preset threshold value to obtain a comparison result; reminding a user to treat the water pollution source when the duty ratio of the safety area is smaller than a set safety threshold value; when the safe area is converted into the light pollution area, the biological community contained in the safe area is driven away;
step 304, monitoring the position of the biological community, determining the safe distance between the water pollution source and the biological community, and if the safe distance is within the corresponding distance threshold, increasing the working power of at least one of the aerator and the filtering device according to a preset proportion.
7. The online sewage monitoring method based on the internet of things according to claim 1, wherein the method comprises the following steps: step 4 comprises: step 401, detecting a water body, obtaining water pollution data output by a floating water quality detector at each position, and marking positions forming the water pollution data; based on water pollution data at each position of the water body, acquiring a plurality of water quality evaluation values, and connecting the positions with equal water quality evaluation values of the water body together to form an equal pollution line;
step 402, judging that the pollution is spreading and the protruding direction of the equal pollution lines is the pollution spreading direction if the number of the equal pollution lines with the water quality evaluation value higher than the second water quality threshold value is increased according to the change of the shape and the density of the equal pollution lines.
8. The online sewage monitoring method based on the internet of things of claim 7, wherein the method comprises the following steps: step 402 is followed by: step 403, acquiring area data of the water body safety area at a plurality of moments, and performing function fitting on the area change trend of the water body safety area to form a water pollution spreading fitting function;
based on the water pollution spreading fitting function, determining the area occupation ratio of the water body safety area at the next moment, and alarming to a user after the area occupation ratio exceeds an alarm threshold;
step 404, determining the position of a biological community in a safety area through a monitoring system, and judging the time required to be consumed for covering the water pollution to the area by combining the water pollution spreading trend to form a first preset time;
step 405, after a first preset time, determining a plurality of areas not higher than the bearing line in the water body, and determining at least one of the areas closest to the water body outlet, and guiding the biota to fall in the safe area to transfer to the water body outlet through the feeding system.
9. The online sewage monitoring method based on the internet of things according to claim 1, wherein the method comprises the following steps: the step 5 comprises the following steps:
step 501, when the pollutant concentration exceeds the bearing line, if the pollutant concentration is still increasing, comprehensively evaluating the pollution degree of the water body to form a safety evaluation value;
step 502, comparing the safety evaluation value with an alert threshold value, judging whether the safety evaluation value is within the alert threshold value, if the safety evaluation value is within the alert threshold value, temporarily avoiding harm to the water body, and preferentially protecting the biological community; if the water is beyond the warning threshold, the water is endangered, an alarm is given to the outside, and the water is treated preferentially;
step 503, after a second preset time, re-judging the water quality evaluation value of the water body, and gradually putting the biological community into the water body according to a preset amount if the water quality evaluation value is falling and is lower than a second water quality threshold value; if the water pollution data concentration does not drop, an alarm is issued.
10. Sewage on-line monitoring system based on thing networking, its characterized in that: comprising the following steps:
the monitoring unit is used for monitoring the water pollution, and sending an early warning to the outside when the water pollution degree exceeds half of a set biological community bearing line after the monitoring data are acquired;
the assessment unit is used for assessing the water pollution degree based on the water pollution data in the water body area, and sending an early warning to a user when the area exceeds half of the bearing line;
the early warning unit is used for reducing pollutants in the water body area, and if the expected effect cannot be achieved, the biological community is driven away from the area to remind a user to treat the water pollution source;
the judging unit is used for judging whether the water pollution is spread to other areas or not when the user does not effectively treat the water pollution source, and determining the spreading trend if the water pollution is spread; if the spreading trend exceeds the expected value, alarming the change of the water quality;
and the alarm unit is used for evaluating the safety of the water body area and sending an alarm to the outside when the evaluation result shows that the water body environment has danger.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116556294A (en) * | 2023-07-04 | 2023-08-08 | 苏州北控环保科技有限公司 | River water ecological treatment equipment and river water ecological treatment method |
| CN117371873A (en) * | 2023-12-01 | 2024-01-09 | 四川省生态环境科学研究院 | Sewage assessment method for environmental protection engineering based on big data |
| CN117886381A (en) * | 2024-03-13 | 2024-04-16 | 甘肃省水利水电勘测设计研究院有限责任公司 | Water treatment agent adding control method and system |
| CN117886381B (en) * | 2024-03-13 | 2024-05-14 | 甘肃省水利水电勘测设计研究院有限责任公司 | Water treatment agent adding control method and system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112734694A (en) * | 2020-12-19 | 2021-04-30 | 闫耀伟 | Water quality monitoring method based on big data |
| CN113219147A (en) * | 2021-05-14 | 2021-08-06 | 南阳理工学院 | Water pollution big data monitoring and early warning device and method |
| CN114878772A (en) * | 2022-06-07 | 2022-08-09 | 中国水利水电科学研究院 | Detection early warning monitoring system applied to sewage treatment |
| CN115825368A (en) * | 2022-12-26 | 2023-03-21 | 南京市水产科学研究所 | Water quality monitoring method and system for aquaculture industry based on Internet of things |
| CN116050951A (en) * | 2023-04-03 | 2023-05-02 | 云南碧翔物联网科技有限公司 | Pollution monitoring method and system based on data analysis model |
-
2023
- 2023-04-11 CN CN202310379327.3A patent/CN116125027B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112734694A (en) * | 2020-12-19 | 2021-04-30 | 闫耀伟 | Water quality monitoring method based on big data |
| CN113219147A (en) * | 2021-05-14 | 2021-08-06 | 南阳理工学院 | Water pollution big data monitoring and early warning device and method |
| CN114878772A (en) * | 2022-06-07 | 2022-08-09 | 中国水利水电科学研究院 | Detection early warning monitoring system applied to sewage treatment |
| CN115825368A (en) * | 2022-12-26 | 2023-03-21 | 南京市水产科学研究所 | Water quality monitoring method and system for aquaculture industry based on Internet of things |
| CN116050951A (en) * | 2023-04-03 | 2023-05-02 | 云南碧翔物联网科技有限公司 | Pollution monitoring method and system based on data analysis model |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116556294A (en) * | 2023-07-04 | 2023-08-08 | 苏州北控环保科技有限公司 | River water ecological treatment equipment and river water ecological treatment method |
| CN116556294B (en) * | 2023-07-04 | 2023-10-17 | 苏州北控环保科技有限公司 | River water ecological treatment equipment and river water ecological treatment method |
| CN117371873A (en) * | 2023-12-01 | 2024-01-09 | 四川省生态环境科学研究院 | Sewage assessment method for environmental protection engineering based on big data |
| CN117371873B (en) * | 2023-12-01 | 2024-03-26 | 四川省生态环境科学研究院 | Sewage assessment method for environmental protection engineering based on big data |
| CN117886381A (en) * | 2024-03-13 | 2024-04-16 | 甘肃省水利水电勘测设计研究院有限责任公司 | Water treatment agent adding control method and system |
| CN117886381B (en) * | 2024-03-13 | 2024-05-14 | 甘肃省水利水电勘测设计研究院有限责任公司 | Water treatment agent adding control method and system |
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